Search Results for author:
Found 6 papers, 2 papers with code
Basis restricted elastic shape analysis on the space of unregistered surfaces
The use of such bases allows to simplify the representation of the corresponding shape space to a finite dimensional latent space.
VariGrad: A Novel Feature Vector Architecture for Geometric Deep Learning on Unregistered Data
We present a novel geometric deep learning layer that leverages the varifold gradient (VariGrad) to compute feature vector representations of 3D geometric data.
Toward Mesh-Invariant 3D Generative Deep Learning with Geometric Measures
3D generative modeling is accelerating as the technology allowing the capture of geometric data is developing.
BaRe-ESA: A Riemannian Framework for Unregistered Human Body Shapes
We present Basis Restricted Elastic Shape Analysis (BaRe-ESA), a novel Riemannian framework for human body scan representation, interpolation and extrapolation.
3D Shape Sequence of Human Comparison and Classification using Current and Varifolds
In this paper we address the task of the comparison and the classification of 3D shape sequences of human.
A Riemannian Framework for Analysis of Human Body Surface
We treat a human body surface as a point in a "shape space" equipped with a family of Riemannian metrics.
